impact of agricultural research in sub-saharan africa
DESCRIPTION
Poverty trends in SSA,Productivity Growth in African Agriculture,Maize Research in WCA,Maize research benefits attributable to IITATRANSCRIPT
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
Impact of Agricultural Research
in Sub-Saharan Africa
Arega D. Alene
R4D Planning Meeting, 23 November 2009, Ibadan, Nigeria
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
Pathway: R&D Productivity Poverty
Technology
Aggregate production
Consumer prices
R&D
Poverty
Productivity
On-farm consumption
Incomes
Health/Nutrition
Labor demand & wages
Non-farm earnings
Economy-wide effects
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
R&D Investments
400
425
450
475
500
525
550
575
600
19
80
19
81
19
82
19
83
19
84
19
85
19
86
19
87
19
88
19
89
19
90
19
91
19
92
19
93
19
94
19
95
19
96
19
97
19
98
19
99
20
00
20
01
20
02
20
03
Exp
end
itu
re (
mil
lion
s of
2000 $
)
0
10
20
30
40
50
601970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
Exp
end
itu
re (
mil
lion
s of
2000 $
)
Source:
Alston et al. (2006)
Beintema and Stads (2006)
Maredia and Raitzer (2006)
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
Poverty trends in SSA
Source: Chen and Ravallion (2007).0
10
20
30
40
50
60
70
80
1981
1984
1987
1990
1993
1996
1999
2000
2001
2002
2004
Year
Po
verty
in
cid
en
ce (
%)
Benin
Nigeria
Burkina Faso
Cameroon
Cote d'Ivoire
Ghana
Senegal
Mali
100
125
150
175
200
225
250
275
300
325
350
40
41
42
43
44
45
46
47
48
49
50
1981 1984 1987 1990 1993 1996 1999 2002 2004
Nu
mb
er o
f p
oor
(mil
lion
))
Po
ver
ty i
nci
den
ce (
%)
Year
# of Poor
% Poor
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
Measuring Total Factor ProductivityNon-parametric distance functions—GAMS (>7,000 equations)
Source: Nin et al. (2003), Journal of Development Economics.
Contemporaneous Sequential
1/ 21 1 1 1 1
1 1
1 1 1 1
( , ) ( , ) ( , )( , , , )
( , ) ( , ) ( , )
t t t t t t t t t
t t t t o o o
o t t t t t t t t t
o o o
D y x D y x D y xM y x y x
D y x D y x D y x
Eff. change Tech. progress
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
Productivity Growth in African Agriculture
Conventional vs. Improved estimates
Conventional estimates
-15
-10
-5
0
5
10
15
20
19
71
19
72
19
73
19
74
19
75
19
76
19
77
19
78
19
79
19
80
19
81
19
82
19
83
19
84
19
85
19
86
19
87
19
88
19
89
19
90
19
91
19
92
19
93
19
94
19
95
19
96
19
97
19
98
19
99
20
00
20
01
20
02
20
03
20
04
Cu
mu
lativ
e g
ro
wth
(%
))
TFP growth
Efficiency change
Technical progress
New estimates
-20
-10
0
10
20
30
40
50
60
70
19
71
19
72
19
73
19
74
19
75
19
76
19
77
19
78
19
79
19
80
19
81
19
82
19
83
19
84
19
85
19
86
19
87
19
88
19
89
19
90
19
91
19
92
19
93
19
94
19
95
19
96
19
97
19
98
19
99
20
00
20
01
20
02
20
03
20
04
Cu
mu
la
tiv
e g
ro
wth
(%
)
Technical progress
TFP growth
Efficiency change
0.3% per year Africa –1.8% per year
SSA – 1.6% per year
Stronger recovery of agric. productivity than conventional measures would suggest
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
0 1( ) 1
0
2
2 3 4
2
5 1 6 7
ln( ) + ln(R&D) ln(Weather)
ln(Labor/ha) ln(Labor/ha) ln(Literacy)
ln(Trade) ( ) ( )
L
j t j
j
t
TFP
t t e
Explaining total factor productivity
162
0 1 2
0 0
16 16
0 1
0 0
162
2
0
ln(R&D/ha) ( ) ln(R&D/ha)
= ln(R&D/ha) ln(R&D/ha)
ln(R&D/ha)
L
j t j t j
j j
t j t j
j j
t j
j
j j
j
j
Explicit modelling of the length & shape of R&D lagPolynomial Distributed Lag Vs. Trapezoid
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
Explaining agricultural productivity (N=15)
Alternative R&D lag specifications (Fixed Effects: Hausman rejects RE)
Variable Trapezoid
(2─16)
Constrained PDL
(0─16)
Unconstrained PDL
(3─16)
Coefficient t-value Coefficient t-value Coefficient t-value
R&Dt 0.0019 1.65*
R&Dt–1 0.0030 1.65*
R&Dt–2 0 0.0041 1.65*
R&Dt–3 0.0025 1.83* 0.0050 1.65* –0.0104 –1.09
R&Dt–4 0.0050 1.83* 0.0058 1.65* –0.0016 –0.39
R&Dt–5 0.0075 1.83* 0.0065 1.65* 0.0060 0.61
R&Dt–6 0.0100 1.83* 0.0071 1.65* 0.0124 1.52
R&Dt–7 0.0125 1.83* 0.0076 1.65* 0.0176 2.05**
R&Dt–8 0.0125 1.83* 0.0080 1.65* 0.0216 2.33**
R&Dt–9 0.0125 1.83* 0.0082 1.65* 0.0244 2.48**
R&Dt–10 0.0125 1.83* 0.0084 1.65* 0.0260 2.58**
R&Dt–11 0.0125 1.83* 0.0084 1.65* 0.0264 2.64**
R&Dt–12 0.0100 1.83* 0.0084 1.65* 0.0256 2.63**
R&Dt–13 0.0075 1.83* 0.0082 1.65* 0.0236 2.43**
R&Dt–14 0.0050 1.83* 0.0079 1.65* 0.0204 1.79*
R&Dt–15 0.0025 1.83* 0.0075 1.65* 0.0160 0.78
R&Dt–16 0 0.0070 1.65* 0.0104 0.01
∑j R&Dt–j 0.11 0.10 0.20
Weather 0.166 2.82*** 0.161 2.74*** 0.167 2.82***
Labor/ha 0.319 1.15 0.290 1.05 0.389 1.39
(Labor/ha)2 0.035 0.71 0.036 0.72 0.044 0.87
Literacy 0.016 0.18 0.014 0.16 0.022 0.25
Trade 0.188 3.31*** 0.192 3.37*** 0.176 3.08***
Time trend –0.003 –0.11 –0.003 –0.12 –0.002 –0.07
(Time trend)2 –0.001 –0.18 –0.001 –0.14 –0.001 –0.29
Constant –1.854 –2.31** –1.856 –2.31** –1.745 –2.18**
R2 0.80 0.80 0.88
Log likelihood 168 168 170
AIC –318 –317 –318
SBIC –288 –288 –282
R&Dε = 0.20
Weatherε = 0.17
Reformsε = 0.18
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
Weather and agricultural productivity
TFPR&D (t−10)
0.960
0.975
0.990
1.005
1.020
1.035
1.050
800
850
900
950
1000
1050
1100
19
71
19
72
19
73
19
74
19
75
19
76
19
77
19
78
19
79
19
80
19
81
19
82
19
83
19
84
19
85
19
86
19
87
19
88
19
89
19
90
19
91
19
92
19
93
19
94
19
95
19
96
19
97
19
98
19
99
20
00
TFP IndexRainfall (mm/year)
TFP
Rainfall
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
R&D and Productivity
-0.5
0.0
0.5
1.0
1.5
2.0
2.5
-1
0
1
2
3
4
51
98
5
19
86
19
87
19
88
19
89
19
90
19
91
19
92
19
93
19
94
19
95
19
96
19
97
19
98
19
99
20
00
20
01
20
02
20
03
R&D growth (%) TFP growth (%)
TFP
R&D (t−10)
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
Aggregate Rate of Return
Model G. lag
(years)
Elasticity ROR
(%)
Trapezoid
3 0.11 27
1 0.10 34
C. PDL
3 0.10 31
0 0.10 44
UC. PDL
3 0.20 33
0 0.10 39
0.000
0.005
0.010
0.015
0.020
0.025
0.030
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
Lag weights
Years
Unconstrained PDL 3–16 Constrained PDL 3–16
Trapezoid 2–16 Constrained PDL 0–16
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
System of Equations
Pathway: R&D... Productivity… Incomes... Poverty
R&D: Polynomial Distributed Lag
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
Equation/variable Parameter Estimate (t-value)
Value added per hectare: α1j + α2j
Research expenditures (t) α1(0) 0.003 (2.34)** 0.007 (4.14)***
Research expenditures (t –1) α1(1) 0.006 (2.34)** 0.012 (4.14)***
Research expenditures (t –2) α1(2) 0.008 (2.34)** 0.018 (4.14)***
Research expenditures (t –3) α1(3) 0.010 (2.34)** 0.022 (4.14)***
Research expenditures (t –4) α1(4) 0.012 (2.34)** 0.025 (4.14)***
Research expenditures (t –5) α1(5) 0.013 (2.34)** 0.028 (4.14)***
Research expenditures (t –6) α1(6) 0.014 (2.34)** 0.030 (4.14)***
Research expenditures (t –7) α1(7) 0.014 (2.34)** 0.031 (4.14)***
Research expenditures (t –8) α1(8) 0.015 (2.34)** 0.032 (4.14)***
Research expenditures (t –9) α1(9) 0.014 (2.34)** 0.031 (4.14)***
Research expenditures (t –10) α1(10) 0.014 (2.34)** 0.030 (4.14)***
Research expenditures (t –11) α1(11) 0.013 (2.34)** 0.028 (4.14)***
Research expenditures (t –12) α1(12) 0.012 (2.34)** 0.025 (4.14)***
Research expenditures (t –13) α1(13) 0.010 (2.34)** 0.022 (4.14)***
Research expenditures (t –14) α1(14) 0.008 (2.34)** 0.018 (4.14)***
Research expenditures (t –15) α1(15) 0.006 (2.34)** 0.012 (4.14)***
Research expenditures (t–16) α1(16) 0.003 (2.34)** 0.007 (4.14)***
Total elasticity
α1(RE)
0.17 (2.34)**
0.38 (4.14)*** (αRE)
Fertilizer (kg per hectare) αFR 0.086 (1.89)*
Labor (workers per hectare) αLB 0.699 (10.01)***
Machinery (tractors per hectare) αMA 0.235 (3.31)***
Irrigation (% of crop land) αIR 0.012 (0.23)
West and Central Africa αWCA 0.457 (3.57)***
Constant δ0 5.161 (23.27)***
R2 0.76
GDP per capita:
Value added per hectare βVA 0.954 (8.49)***
Land (hectares per worker) βLA 1.008 (9.82)***
Government expenditures (% of GDP) βGE 0.215 (1.78)*
Fixed capital investment (% of GDP) βFI –0.005 (–0.05)
Rural population (% of total) βPR –0.653 (–2.28)**
West and Central Africa βWCA –0.313 (–3.35)***
Constant β0 0.638 (0.95)***
R2 0.76
Poverty:
Gini coefficient of inequality γGC 1.740 (3.78)***
GDP per capita γGDP –0.593 (–5.81)***
Government expenditures (% of GDP) γGE 0.226 (1.18)
Fixed capital investment (% of GDP) γFI 0.078 (0.51)
Population growth (% per year) γPG 0.229 (1.43)
West and Central Africa γWCA –0.076 (–0.59)
Constant γ 0 8.903 (8.47)***
R2 0.31
Simultaneous equation system estimates
of the impact of R&D in SSA
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
Elasticity of—with respect to Estimate
(1) Productivity — R&D 0.38
(2) GDP per capita — Productivity 0.95
(3) Poverty — GDP per capita –0.60
(4) GDP per capita — R&D = (1) (2) 0.36
(5) Poverty — Productivity = (2) (3) –0.58
(6) Poverty — R&D = (1) (2) (3) –0.22
Elasticity Measures
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
Poverty impacts of R&D in SSA
Annual poverty reduction = 2.3 million (0.8% of the poor)
Poverty reduction due to IITA: 0.5 to 1 million per year
Doubling R&D investments, given more efficient support services:
o Poverty reduction of 2 percentage points per year
o Equivalent to 4.8% of the poor
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
April 2009
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
Maize Area & Yields
0
2
4
6
8
101
97
11
97
21
97
31
97
41
97
51
97
61
97
71
97
81
97
91
98
01
98
11
98
21
98
31
98
41
98
51
98
61
98
71
98
81
98
91
99
01
99
11
99
21
99
31
99
41
99
51
99
61
99
71
99
81
99
92
00
02
00
12
00
22
00
32
00
42
00
5
Year
Area
(m
illi
on
ha
)
0.0
0.5
1.0
1.5
2.0
2.5
Yie
ld (
t/h
a)
Area
Yield
Case Study Evidence: Maize Research in WCA
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
Maize varieties released in WCA, 1965–2006
Country Maize varieties released
Nigeria 82
Burkina Faso 59
Benin 29
Cameroon 27
Ghana 36
Togo 27
Senegal 47
Mali 18
Côte d’Ivoire 8
Chad 14
D.R. Congo 20
Guinea 12
Total 379
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
Adoption of improved maize varieties in WCA
Area under improved varieties ('000 ha) % maize area Country
1981 2005 2005
Nigeria 27 2180 66
Mali 2 163 38
Burkina Faso 5 333 76
Cameroon 36 244 46
Ghana 5 664 88
Senegal 3 136 95
Benin 10 236 42
Togo 3 213 50
Côte d’Ivoire 20 69 53
WCA 111 4238 62
IITA varieties account for 43% of area under MVs
0
10
20
30
40
50
60
70
80
90
100
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
Year
Ad
op
tio
n r
ate (
% a
rea
)
Nigeria
Mali
Burkina Faso
Cameroon
Ghana
Senegal
Benin
Togo
Cote d'Ivoire
Aggregate
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
Production with & without maize research
0
2
4
6
8
10
12
14
16
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
Pro
du
cti
on
(m
illi
on
to
ns)
Actual
Counterfactual
Maize
0
2
4
6
8
10
12
14
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
Pro
du
cti
on
(m
illi
on
to
ns)
Actual
Counterfactual
Sorghum
0
2
4
6
8
10
12
14
16
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
Pro
du
ctio
n (
mil
lion
ton
s)
Millet
Actual
Counterfactual
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
Maize Research Benefits & Costs
Summary Measures
Annual benefits
(US$ million)
Benefit–Cost
ratio
Rate of Return
(%)
Nigeria 194 84 74
Mali 6 11 37
Burkina Faso 10 14 39
Cameroon 15 18 69
Ghana 24 12 40
Senegal 5 12 28
Benin 8 28 64
Togo 5 10 31
Côte d’Ivoire 13 20 63
Aggregate 274 21 43
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
Maize research benefits attributable to IITA(US$ million)
US$90–126 m/year
0
50
100
150
200
250
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
Poverty reduction due to maize research at IITA(‘000)
0
100
200
300
400
500
600
Pover
ty r
edu
ctio
n (
'000)
230–326,000/year
35–50,000/$1 million
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
September 2009
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
Stronger recovery of agricultural productivity after mid-1980s
Results confirm the key roles of R&D, weather, and policy reforms
R&D has contributed to productivity growth and poverty reduction
Potential impacts are greater (fix inefficiencies outside R&D system)
SSA spends half of India’s & a quarter of US R&D expenditures
Increased R&D investments would bring about greater poverty reduction
Increased investments in extension/credit/input supply systems
o Infrastructure, institutions, credit, subsidies, etc
o Greater physical and economic access to seed & fertilizer
Enhancing poverty reduction through resource reallocation (…)
o Current allocations are suboptimal
Conclusions & Recommendations
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
Benefits to Poor Households
Resource allocation based on expected impact
0
5
10
15
20
25
30
35
40
45
50
0 10 20 30 40 50 60 70 80 90 100
Cumulative research costs (% of total budget)
Cu
mu
lati
ve
ben
efit
s to
th
e p
oo
r
(%
of
tota
l re
sea
rch
ben
efit
s)
Equity
Actual
Efficiency
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
Implied Resource Re-allocation
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
January 2009
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
Thank You